Perceptual quality assessment plays a vital role in the visual communication systems owing
to the existence of quality degradations introduced in various stages of visual signal …

Establishing an accurate objective evaluation metric of image sharpness is crucial for image
analysis, recognition and quality measurement. In this review, we highlight recent advances …

The difficulty of no-reference image quality assessment (NR IQA) often lies in the lack of
knowledge about the distortion in the image, which makes quality assessment blind and …

Most publicly available image quality databases have been created under highly controlled
conditions by introducing graded simulated distortions onto high-quality photographs …

This paper describes a recently created image database, TID2013, intended for evaluation
of full-reference visual quality assessment metrics. With respect to TID2008, the new …

In this paper, we investigate into the problem of image quality assessment (IQA) and
enhancement via machine learning. This issue has long attracted a wide range of attention …

Anatomical landmark segmentation and pathology localisation are important steps in
automated analysis of medical images. They are particularly challenging when the anatomy …

Traditional full-reference image quality assessment (IQA) metrics generally predict the
quality of the distorted image by measuring its deviation from a perfect quality image called …

Low-dose computed tomography (LDCT) has offered tremendous benefits in radiation-
restricted applications, but the quantum noise as resulted by the insufficient number of …

In this work, we investigate the use of deep learning for distortion-generic blind image
quality assessment. We report on different design choices, ranging from the use of features …